File size: 2,991 Bytes
90f8324
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
---

library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: results
  results: []
---


<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# results

This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7669

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05

- train_batch_size: 16

- eval_batch_size: 16

- seed: 42

- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments

- lr_scheduler_type: linear

- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 12.8436       | 1.0   | 4    | 11.5652         |
| 12.8436       | 2.0   | 8    | 8.6499          |
| 12.8436       | 3.0   | 12   | 6.6430          |
| 12.8436       | 4.0   | 16   | 5.4425          |
| 12.8436       | 5.0   | 20   | 4.4521          |
| 12.8436       | 6.0   | 24   | 3.9127          |
| 12.8436       | 7.0   | 28   | 3.3273          |
| 12.8436       | 8.0   | 32   | 3.0743          |
| 12.8436       | 9.0   | 36   | 2.8087          |
| 12.8436       | 10.0  | 40   | 2.5618          |
| 12.8436       | 11.0  | 44   | 2.4515          |
| 12.8436       | 12.0  | 48   | 2.3580          |
| 12.8436       | 13.0  | 52   | 2.2749          |
| 12.8436       | 14.0  | 56   | 2.1216          |
| 12.8436       | 15.0  | 60   | 2.0890          |
| 12.8436       | 16.0  | 64   | 2.0283          |
| 12.8436       | 17.0  | 68   | 2.0358          |
| 12.8436       | 18.0  | 72   | 1.9374          |
| 12.8436       | 19.0  | 76   | 1.9090          |
| 12.8436       | 20.0  | 80   | 1.8779          |
| 12.8436       | 21.0  | 84   | 1.8474          |
| 12.8436       | 22.0  | 88   | 1.8371          |
| 12.8436       | 23.0  | 92   | 1.8247          |
| 12.8436       | 24.0  | 96   | 1.8031          |
| 12.8436       | 25.0  | 100  | 1.7836          |
| 12.8436       | 26.0  | 104  | 1.7500          |
| 12.8436       | 27.0  | 108  | 1.7332          |
| 12.8436       | 28.0  | 112  | 1.7477          |
| 12.8436       | 29.0  | 116  | 1.7634          |
| 12.8436       | 30.0  | 120  | 1.7669          |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cpu
- Datasets 3.3.2
- Tokenizers 0.21.0